We find that the magnitudes of the regional effects of monetary policy were considerably dampened during the Volcker-Greenspan era. Further, regional differences in the depths of monetary-policy-induced recessions are related to the concentration of the banking sector, whereas differences in the...

We analyze the relationship between housing and the business cycle in a set of 51 U.S. cities. Most surprisingly, we find that declines in house prices are often not followed by declines in employment. We also find that national permits are a better leading indicator for a city's employment than...

In this paper, we propose a new family of multivariate loss functions that can be used to test the rationality of vector forecasts without assuming independence across individual variables. When only one variable is of interest, the loss function reduces to the flexible asymmetric family...

We jointly test the rationality of the Federal Reserve’s Greenbook forecasts of infiation, unemployment, and output growth using a multivariate nonseparable asymmetric loss function. We find that the forecasts are rationalizable and exhibit directional asymmetry. The degree of asymmetry...

In this paper, we propose a new family of multivariate loss functions to test the rationality of vector forecasts without assuming independence across variables. When only one variable is of interest, the loss function reduces to the flexible asymmetric family proposed by Elliott, Komunjer, and...

In situations where a sequence of forecasts is observed, a common strategy is to examine “rationality” conditional on a given loss function. We examine this from a different perspective— supposing that we have a family of loss functions indexed by unknown shape parameters, then given the...

This paper proposes a method for comparing and combining conditional quantile forecasts in an out-of-sample framework. We construct a Conditional Quantile Forecast Encompassing (CQFE) test as a Wald-type test of superior predictive ability. Rejection of CQFE provides a basis for combination of...

This paper derives necessary and sufficient conditions for nonparametric transformation models to be (i) correctly specified, and (ii) identified. Our correct specification conditions come in a form of partial differential equations; when satisfied by the true distribution, they ensure that the...

This paper establishes the identifiability of the parameters of the Box-Cox model under restrictions that do not require the disturbance in the model to be independent of the explanatory variables. The proposed restrictions are semiparametric in nature: they restrict the support of the...